Data-driven remaining useful life estimation for milling process: sensors, algorithms, datasets, and future directions S Sayyad, S Kumar, A Bongale, P Kamat, S Patil, K Kotecha IEEE Access 9, 110255-110286, 2021 | 64 | 2021 |
Fault detection in induction motor using time domain and spectral imaging-based transfer learning approach on vibration data S Misra, S Kumar, S Sayyad, A Bongale, P Jadhav, K Kotecha, ... Sensors 22 (21), 8210, 2022 | 29 | 2022 |
Estimating remaining useful life in machines using artificial intelligence: A scoping review S Sayyad, S Kumar, A Bongale, AM Bongale, S Patil Libr. Philos. Pract 2021, 1-26, 2021 | 19 | 2021 |
Tool wear prediction using long short-term memory variants and hybrid feature selection techniques S Sayyad, S Kumar, A Bongale, K Kotecha, G Selvachandran, ... The International Journal of Advanced Manufacturing Technology 121 (9), 6611 …, 2022 | 17 | 2022 |
Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time–Frequency-Based Features and Deep Learning Models S Sayyad, S Kumar, A Bongale, K Kotecha, A Abraham Sensors 23 (12), 5659, 2023 | 5 | 2023 |
Systematic Study of Digital Twins for Welding Processes V Warke, S Sayyad, S Kumar, A Bongale, R Suresh Advanced Joining Technologies, 203-215, 0 | | |